How optimal are the binding energetics of barnase and barstar?

The extracellular ribonuclease barnase and its intracellular inhibitor barstar bind fast and with high affinity. Although extensive experimental and theoretical studies have been carried out on this system, it is unclear what the relative importance of different contributions to the high affinity is and whether binding can be improved through point mutations. In this work, we first applied Poisson-Boltzmann electrostatic calculations to 65 barnase-barstar complexes with mutations in both barnase and barstar. The continuum electrostatic calculations with a van der Waals surface dielectric boundary definition result in the electrostatic interaction free energy providing the dominant contribution favoring barnase-barstar binding. The results show that the computed electrostatic binding free energy can be improved through mutations at W44/barstar and E73/barnase. Furthermore, the determinants of binding affinity were quantified by applying COMparative BINding Energy (COMBINE) analysis to derive quantitative structure-activity relationships (QSARs) for the 65 complexes. The COMBINE QSAR model highlights approximately 20 interfacial residue pairs as responsible for most of the differences in binding affinity between the mutant complexes, mainly due to electrostatic interactions. Based on the COMBINE model, together with Brownian dynamics simulations to compute diffusional association rate constants, several mutants were designed to have higher binding affinities than the wild-type proteins.     

Diffusional encounter of barnase and barstar

We present an analysis of trajectories from Brownian dynamics simulations of diffusional protein-protein encounter for the well-studied system of barnase and barstar. This analysis reveals details about the optimal association pathways, the regions of the encounter complex, possible differences of the pathways for dissociation and association, the coupling of translational and rotation motion, and the effect of mutations on the trajectories. We found that a small free-energy barrier divides the energetically most favorable region into a region of the encounter complex above the barnase binding interface and a region around a second energy minimum near the RNA binding loop. When entering the region of the encounter complex from the region near the RNA binding loop, barstar has to change its orientation to increase the electrostatic attraction between the proteins. By concentrating the analysis on the successful binding trajectories, we found that the region of the second minimum is not essential for the binding of barstar to barnase. Nevertheless, this region may be helpful to steer barstar into the region of the encounter complex. When applying the same analysis to several barnase mutants, we found that single mutations may drastically change the free-energy landscape and may significantly alter the population of the two minima. Therefore, certain protein-protein pairs may require careful adaptation of the positions of encounter and transition states when interpreting mutation effects on kinetic rates of association and/or dissociation.     

Fatigue effect on cross-talk in mechanomyography signals of extensor and flexor forearm muscles during maximal voluntary isometric contractions

Objective:This paper presents the analyses of the fatigue effect on the cross-talk in mechanomyography (MMG) signals of extensor and flexor forearm muscles during pre- and post-fatigue maximum voluntary isometric contraction (MVIC).Methods:Twenty male participants performed repetitive submaximal (60% MVIC) grip muscle contractions to induce muscle fatigue and the results were analyzed during the pre- and post-fatigue MVIC. MMG signals were recorded on the extensor digitorum (ED), extensor carpi radialis longus (ECRL), flexor digitorum superficialis (FDS) and flexor carpi radialis (FCR) muscles. The cross-correlation coefficient was used to quantify the cross-talk values in forearm muscle pairs (MP1, MP2, MP3, MP4, MP5 and MP6). In addition, the MMG RMS and MMG MPF were calculated to determine force production and muscle fatigue level, respectively.Results:The fatigue effect significantly increased the cross-talk values in forearm muscle pairs except for MP2 and MP6. While the MMG RMS and MMG MPF significantly decreased (p<0.05) based on the examination of the mean differences from pre- and post-fatigue MVIC.Conclusion:The presented results can be used as a reference for further investigation of cross-talk on the fatigue assessment of extensor and flexor muscles’ mechanic.     

Protein-protein docking by simulating the process of association subject to biochemical constraints

We present a computational procedure for modeling protein-protein association and predicting the structures of protein-protein complexes. The initial sampling stage is based on an efficient Brownian dynamics algorithm that mimics the physical process of diffusional association. Relevant biochemical data can be directly incorporated as distance constraints at this stage. The docked configurations are then grouped with a hierarchical clustering algorithm into ensembles that represent potential protein-protein encounter complexes. Flexible refinement of selected representative structures is done by molecular dynamics simulation. The protein-protein docking procedure was thoroughly tested on 10 structurally and functionally diverse protein-protein complexes. Starting from X-ray crystal structures of the unbound proteins, in 9 out of 10 cases it yields structures of protein-protein complexes close to those determined experimentally with the percentage of correct contacts >30% and interface backbone RMSD <4 A. Detailed examination of all the docking cases gives insights into important determinants of the performance of the computational approach in modeling protein-protein association and predicting of protein-protein complex structures.     

Concerted simulations reveal how peroxidase compound III formation results in cellular oscillations

A major problem in mathematical modeling of the dynamics of complex biological systems is the frequent lack of knowledge of kinetic parameters. Here, we apply Brownian dynamics simulations, based on protein three-dimensional structures, to estimate a previously undetermined kinetic parameter, which is then used in biochemical network simulations. The peroxidase-oxidase reaction involves many elementary steps and displays oscillatory dynamics important for immune response. Brownian dynamics simulations were performed for three different peroxidases to estimate the rate constant for one of the elementary steps crucial for oscillations in the peroxidase-oxidase reaction, the association of superoxide with peroxidase. Computed second-order rate constants agree well with available experimental data and permit prediction of rate constants at physiological conditions. The simulations show that electrostatic interactions depress the rate of superoxide association with myeloperoxidase, bringing it into the range necessary for oscillatory behavior in activated neutrophils. Such negative electrostatic steering of enzyme-substrate association presents a novel control mechanism and lies in sharp contrast to the electrostatically-steered fast association of superoxide and Cu/Zn superoxide dismutase, which is also simulated here. The results demonstrate the potential of an integrated and concerted application of structure-based simulations and biochemical network simulations in cellular systems biology.     

Ionic liquid-based microwave-assisted extraction of lipid and eicosapentaenoic acid from Nannochloropsis oceanica biomass: experimental optimization approach

Journal of Applied Phycology - Lipids and eicosapentaenoic acid (EPA) compounds from Nannochloropsis oceanica biomass were extracted using a combination of ionic liquids (ILs) and...     

Proteasomal degradation of p130 facilitate cell cycle deregulation and impairment of cellular differentiation in high-risk Human Papillomavirus 16 and 18 E7 transfected cells

Molecular Biology Reports - The High-Risk Human Papillomaviruses (HR-HPVs) 16 and 18 are known to cause cervical cancer, which is primarily attributed to E6 and E7 oncoproteins. In addition, recent...     

On the structure and dynamics of the complex of the nucleosome and the linker histone

Several different models of the linker histone (LH)–nucleosome complex have been proposed, but none of them has unambiguously revealed the position and binding sites of the LH on the nucleosome. Using Brownian dynamics-based docking together with normal mode analysis of the nucleosome to account for the flexibility of two flanking 10 bp long linker DNAs (L-DNA), we identified binding modes of the H5-LH globular domain (GH5) to the nucleosome. For a wide range of nucleosomal conformations with the L-DNA ends less than 65 Å apart, one dominant binding mode was identified for GH5 and found to be consistent with fluorescence recovery after photobleaching (FRAP) experiments. GH5 binds asymmetrically with respect to the nucleosomal dyad axis, fitting between the nucleosomal DNA and one of the L-DNAs. For greater distances between L-DNA ends, docking of GH5 to the L-DNA that is more restrained and less open becomes favored. These results suggest a selection mechanism by which GH5 preferentially binds one of the L-DNAs and thereby affects DNA dynamics and accessibility and contributes to formation of a particular chromatin fiber structure. The two binding modes identified would, respectively, favor a tight zigzag chromatin structure or a loose solenoid chromatin fiber.     

A universal code for RNA recognition by PUF proteins

The design of proteins that can bind any RNA sequence of interest has many potential biological and medical applications. Here we have expanded the recognition of Pumilio and FBF homology protein (PUF) repeats beyond adenine, guanine and uracil and evolved them to specifically bind cytosine. These repeat sequences can be used to create PUF domains capable of selectively binding RNA targets of diverse sequence and structure.